UAV-Based Observation and Big Data Analytics for Traffic Flow Estimation: A Comparative and Complementary Approach

In recent years, unmanned aerial vehicles (UAVs) and Big Data analytics have both emerged as increasingly important approaches in advanced traffic monitoring. UAVs provide high-resolution spatial data and operational flexibility, supporting automated vehicle detection and the construction of origin–destination (O/D) matrices through video processing. Conversely, Big Data offers a passive and non-invasive approach based on heterogeneous sources such as mobile devices, satellite navigation systems, and digital applications, ensuring continuous temporal coverage for mobility pattern analysis. This study evaluates the combined use of UAVs and Big Data for traffic flow monitoring as an alternative to traditional manual methods. Focusing on two case studies in Trapani (Italy), the research assesses the advantages and limitations of each technology and their complementary use. Results show that Big Data effectively captures large-scale temporal dynamics but lacks accuracy for detailed O/D estimation, while UAVs provide precise spatial and behavioural information despite operational constraints. A key objective of this study is to investigate the potential complementarity between UAV observations and Big Data traffic monitoring technologies, highlighting the main strengths and limitations of each method under complex study sites and challenging operational conditions for traffic data acquisition using UAVs.